Applications such as Uber and Lyft depend on location estimates on mobile devices. Passengers awaiting their ride can monitor the progress of their drivers on a map. Passengers provide their pickup locations when requesting their rides.
However, in crowded cities, a passenger pickup location by itself has proved to be insufficient in many cases. For example, there are several documented cases of mistaken identities with passengers getting into the wrong cars or drivers approaching the wrong groups for pickup. Such inaccurate or imprecise pickup location estimates can lead to situations where the drivers and passengers engage in a series of calls or texts to resolve the misidentifications. Such issues may be even more challenging to resolve in situations when there are difficulties in reading license plates at night, when a self-driving taxis being the pickup vehicle, or when a robot being the delivery vehicle. Therefore, it would be beneficial to use apparatuses and methods for peer discovery in transactional mobile applications.